數據庫中可以用datetime、bigint、timestamp來表示時間,那麼選擇什麼類型來存儲時間比較合適呢?
前期數據準備
通過程序往數據庫插入50w數據
數據表:
CREATE TABLE `users` ( `id` int(11) NOT NULL AUTO_INCREMENT, `time_date` datetime NOT NULL, `time_timestamp` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, `time_long` bigint(20) NOT NULL, PRIMARY KEY (`id`), KEY `time_long` (`time_long`), KEY `time_timestamp` (`time_timestamp`), KEY `time_date` (`time_date`) ) ENGINE=InnoDB AUTO_INCREMENT=500003 DEFAULT CHARSET=latin1
其中time_long、time_timestamp、time_date爲同一時間的不同存儲格式
實體類users
/** * @author hetiantian * @date 2018/10/21 * */ @Builder @Data public class Users { /** * 自增唯一id * */ private Long id; /** * date類型的時間 * */ private Date timeDate; /** * timestamp類型的時間 * */ private Timestamp timeTimestamp; /** * long類型的時間 * */ private long timeLong; }
dao層接口
/** * @author hetiantian * @date 2018/10/21 * */ @Mapper public interface UsersMapper { @Insert("insert into users(time_date, time_timestamp, time_long) value(#{timeDate}, #{timeTimestamp}, #{timeLong})") @Options(useGeneratedKeys = true,keyProperty = "id",keyColumn = "id") int saveUsers(Users users); }
測試類往數據庫插入數據
public class UsersMapperTest extends BaseTest { @Resource private UsersMapper usersMapper; @Test public void test() { for (int i = 0; i < 500000; i++) { long time = System.currentTimeMillis(); usersMapper.saveUsers(Users.builder().timeDate(new Date(time)).timeLong(time).timeTimestamp(new Timestamp(time)).build()); } } }
sql查詢速率測試
通過datetime類型查詢:
select count(*) from users where time_date >="2018-10-21 23:32:44" and time_date <="2018-10-21 23:41:22"
耗時:0.171
通過timestamp類型查詢
select count(*) from users where time_timestamp >= "2018-10-21 23:32:44" and time_timestamp <="2018-10-21 23:41:22"
耗時:0.351
通過bigint類型查詢
select count(*) from users where time_long >=1540135964091 and time_long <=1540136482372
耗時:0.130s
結論 在InnoDB存儲引擎下,通過時間範圍查找,性能bigint > datetime > timestamp
sql分組速率測試
使用bigint 進行分組會每條數據進行一個分組,如果將bigint做一個轉化在去分組就沒有比較的意義了,轉化也是需要時間的
通過datetime類型分組:
select time_date, count(*) from users group by time_date
耗時:0.176s
通過timestamp類型分組:
select time_timestamp, count(*) from users group by time_timestamp
耗時:0.173s
結論 在InnoDB存儲引擎下,通過時間分組,性能timestamp > datetime,但是相差不大
sql排序速率測試
通過datetime類型排序:
select * from users order by time_date
耗時:1.038s
通過timestamp類型排序
select * from users order by time_timestamp
耗時:0.933s
通過bigint類型排序
select * from users order by time_long
耗時:0.775s
結論 在InnoDB存儲引擎下,通過時間排序,性能bigint > timestamp > datetime
小結
如果需要對時間字段進行操作(如通過時間範圍查找或者排序等),推薦使用bigint,如果時間字段不需要進行任何操作,推薦使用timestamp,使用4個字節保存比較節省空間,但是隻能記錄到2038年記錄的時間有限。